股海罗盘 - A股股票量化分析

Stock Compass aims to address three core pain points faced by A-share investors: difficulty in verifying signal effectiveness, fragmented analysis across limited dimensions, and challenges in preserving and sharing analytical results. Through its self-learning quantitative engine, it backtests over 600,000 historical signals for each stock and visually displays the historical match rate, enabling users to clearly assess how a specific indicator or signal has performed in the past, thereby reducing blind following.

To use it, simply input a stock code or name. The tool automatically invokes the engine to pull data across 17 dimensions—including market quotes, capital flows, technical indicators, financials, holdings, share unlock events, and research reports—in one go, followed by in-depth analysis. Its core features include generating historical match rate progress bars, uncovering five types of market pattern maps, conducting ETF quadrant linkage analysis, and cross-validating viewpoints from research reports across the entire market, ultimately producing a DOCX report with candlestick charts and analytical conclusions in one click.

This tool is well-suited for A-share market participants who need data to support decisions, wish to validate investment logic, or require efficient production of analytical reports. Whether you are an individual investor, a quantitative researcher, or a finance professional needing to provide clients with professional analysis reports, you can benefit from it.

It is recommended that users treat it as an auxiliary validation tool for investment decisions, not the sole basis. When interpreting the historical match rate, understand that 'past effectiveness does not guarantee future results,' and combine it with the current macroeconomic environment for comprehensive judgment. Generated reports can serve as standardized materials for internal archiving or external communication, enhancing professionalism and efficiency.